1. Field of the Invention
The present invention relates to a method and device for transforming an input image to an output image having a large number of picture elements.
2. Description of the Related Art
Image transform processing has been performed, for example, to enlarge image data for printing or displaying. Ordinarily, interpolation processing is used for enlarging an image. In this interpolation processing, a new picture element is added between picture elements neighboring each other, and the value of each added picture element is set to an averaged value of the picture elements surrounding the picture element to be added. However, the image quality obtained by this interpolation processing is inferior in terms of clarity.
On the other hand, a method of performing image transform with higher accuracy has been also reported (M. F. Barnsley: “Fractal Image Compression”, AK Peters Ltd.). This report describes a technology concerning a method of compressing image data on the basis of Fractal self-similarity theory. Though mention has been made of the data compression method to be used for data storage or transfer in this report, this technology can be also applied directly to image transform processing for enlarging an image. Such applications are described below.
As a first step, an input image consisting of M×N (1<M, N) picture elements (one picture element having k [1<k] bit tone) is divided to a square block (hereinafter referred to as “domain block”) having i×i (1<i<M, N) picture elements. Then, a tetragonal block (referred to as “range block”) of j×j (i<j) picture elements is defined for each domain block. For each range block is defined in the input image, the image within this block is stored. The range block having the image presenting the highest self-similarity to the image within the domain block is found. The self-similarity refers to the similarity between a reduced image of the range block obtained by reducing the range block image to a size of the domain block and the image of the domain block. The similarity is measured by a specified standard. By finding the range block image having the highest self-similarity to each domain block image in the input image and by replacing all the domain block images with the range block image having the highest similarity, an image magnified by j/i times is obtained.
If the domain block image is replaced with a range block image by Fractal transform processing, an image transform with high faithfulness (resolution) within each range block image is obtained. However, because each range block image is extracted from any region within the input image, there is no image continuity in the boundaries of each range block. For this reason, the sequential replacement of all the domain block images with the range block images causes image continuity to be lacking at the boundaries of each range block, presenting a problem in image quality in the boundary region.